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This paper scopes the specialties of a hazard identification study for large and extra-large unmanned undersea vehicles (UUVs). A generic node/function structure is derived from different large and extra-large UUV designs, partially own vehicle designs from research projects, and partially from commercial vehicles. For each node, a short overview of its components and the proper function or operations is defined. A set of guide words is used to prompt a hazard discussion for each node, which identifies unwanted functions, resulting in potential hazards and unmitigated consequences. Related to the SafeMASS-Report from DNV, this work concentrates on selected topics of the bridge-related function on voyage, control & monitoring, and abnormal situations. For unmanned vehicles without any person on board, these three topics become more important for underwater vehicles with very limited connectivity or temporary disruptions of communication whereby an operator in a remote-control center could only be provided with rough vehicle or mission states. Therefore, vehicle control, whether in hard- or software, must handle most tasks belonging to the considered functions automatically or autonomously. Hence, the most appropriate reactions of the system to unwanted system
behavior must be implemented. This HAZID study could, on the one hand, be used as background for such an implementation, and on the other hand, it is used to verify the implemented actions on the risks and hazards.
Information on the condition and reliability of an offshore jacket structure provided by a vibration-based structural health monitoring system can guide decisions on inspection and maintenance. When selecting the sensor setup, the designer of the monitoring system must assess its overall benefit compared to its costs before installation. The potential benefit of continuously monitoring the dynamic response of a jacket structure can be formally quantified through a value of information analysis from Bayesian decision theory. In this contribution, we present a framework for optimizing the placement of vibration sensors on offshore jacket structures by maximizing the value of information of the monitoring system. To solve the resulting discrete optimization problem, we adapt a genetic algorithm. The framework is demonstrated in a numerical example considering a redundant jacket-type steel frame. The numerical study shows that monitoring the vibration response of the frame is beneficial. Good sensor setups consist of relatively few sensors located towards the upper part of the
frame. The adapted genetic algorithm performs similarly well as established sequential sensor placement algorithms and holds substantial promise for application to real jacket structures.
For a comprehensive safety assessment of stationary lithium-ion-battery applications, it is necessary to better understand the consequences of thermal runaway (TR). In this study, experimental tests comprising twelve TR experiments including four single-cell tests, two cell stack tests and six second-life module tests (2.65 kW h and 6.85 kW h) with an NMC-cathode under similar initial conditions were conducted. The temperature (direct at cells/modules and in near field), mass loss, cell/module voltage, and qualitative vent gas composition (Fourier transform infrared (FTIR) and diode laser spectroscopy (DLS) for HF) were measured. The results of the tests showed that the battery TR is accompanied by severe and in some cases violent chemical reactions. In most cases, TR was not accompanied by pregassing of the modules. Jet flames up to a length of 5 m and fragment throwing to distances to more than 30 m were detected. The TR of the tested modules was accompanied by significant mass loss of up to 82%. The maximum HF concentration measured was 76 ppm, whereby the measured HF concentrations in the module tests were not necessarily higher than that in the cell stack tests.
Subsequently, an explosion of the released vent gas occurred in one of the tests, resulting in the intensification of the negative consequences. According to the evaluation of the gas measurements with regard to toxicity base on the “Acute Exposure Guideline Levels” (AEGL), there is some concern with regards to CO, which may be equally as important to consider as the release of HF.
Composition and Explosibility of Gas Emissions from Lithium-Ion Batteries Undergoing Thermal Runaway
(2023)
Lithium-based batteries have the potential to undergo thermal runaway (TR), during which mixtures of gases are released. The purpose of this study was to assess the explosibility of the gaseous emission from LIBs of an NMC-based cathode during thermal runaway. In the current project, a series of pouch lithium-based battery cells was exposed to abuse conditions (thermal) to study the total amount of gases released and the composition of the gas mixture. First, the battery cells were placed in a closed vessel, and the pressure and temperature rise inside the vessel were measured. In a second step, the composition of gases was analysed using a Fourier transform Infrared (FTIR) spectrometer.
We found that the amount of released gases was up to 102 ± 4 L, with a clear dependence on the battery capacity. This study showed that the concentration of gaseous emissions such as carbon monoxide (CO), methane (CH4), ethylene (C2H4), ethane (C2H6), and hydrogen cyanide (HCN) increased with higher cell capacity. Of the five studied flammable gases, the maximum concentrations of carbon monoxide (16.85 vol%), methane (7.6 vol%), and ethylene (7.86 vol%) were identified to be within their explosible range. Applying Le Chatelier’s law, a calculated lower explosion limit (LEL) of 7% in volume fraction was obtained for the gas mixture. The upper explosion limit (UEL) of the gas mixture was also found to be 31% in volume. A filter comprising pyrobubbles was used for the removal of the studied gas components released during the thermal abuse. The investigation revealed that the pyrobubbles filter was highly effect in the removal of HCN (up to 94% removal) and CO2 (up to 100% removal). Herein, we report the dependency of the method of thermal runaway trigger on the measured maximum temperature.
Two hybrid alkaline cements (HAC) based on Portland clinker, ground granulated blast furnace slag (GGBFS), fly ash and sodium sulfate, as well as an alkali-activated GGBFS/fly ash blend and a Portland cement paste were exposed to a saturated saline solution for 70 days. The combined chemical attack of chloride, magnesium and sulfate ions and the associated changes of the phase assemblage of the materials were studied by X-ray diffraction, thermal analysis and spatially resolved X-ray fluorescence spectroscopy. The experimental results revealed dissolution of ettringite, C-N-A-S-H and calcite, and the formation of gypsum, Kuzel's salt and Friedel's salt; thermodynamic modeling indicated the formation of M-S-H. The resistance of the HAC against attack by the saline solution increased with Portland clinker fraction. The capacity of portlandite to maintain pH at values above 10 is found to be a major factor controlling the resistance of HAC against corrosion in the saline solution.
In the present paper, an approach for updating the continuous stress range distribution of a welded connection of a wind turbine support structure with predicted information from strain measurements is presented. Environmental conditions, such as wind or, in offshore fields, waves and currents, in combination with rotor excitations generate cyclic stresses affecting the reliability of welded joints of the support structure over the service life. Using strain measurements, these conditions can be monitored, and the resulting stress ranges, under consideration of measurement, mechanical and material uncertainties, can be reconstructed. These stress ranges can be used as an input for updating the prior probability density function (PDF) of the stress ranges predicted by the overall dynamics and a detailed design analysis. Applying Bayesian probability theory and decision theoretical implications, the predicted posterior probability density of the stress ranges is calculated based on the design information and uncertainties. This approach is exemplified, and it is shown how the predicted stress ranges and the design stress ranges are distributed. The prior and the predicted posterior stress ranges are used for a reliability calculation for potentially entering a pre-posterior decision analysis
The new crack luminescence method offers the possibility of making fatigue surface cracks in metallic materials more visible during inspections through a special coating system. This coating system consists of two layers, whereby the first layer has fluorescent properties and emits visible light as soon as it is irradiated by UV light. The top layer is black and is designed to prevent the fluorescent layer from emitting if no crack develops in the underlying material. The technique proved particularly useful in a wide variety of fatigue tests of steel components under laboratory conditions. Moreover, it has the potential to be used in various industrial applications. To enable industrial deployment and integration into maintenance strategies, a concept study is developed in this contribution, resulting in a qualification framework that can serve as a foundation for determining the reliability of the crack luminescence system in terms of a probability of detection curve. Within this study, factors causing measurement variability and uncertainty are being determined and their influences assessed. Due to the extension of the system by a moving computer vision system for automated crack detection using artificial intelligence, additional long-term effects associated with structural health monitoring systems need to be incorporated into an extended probability of detection study as part of the technical justification. Finally, important aspects and findings related to design of experiments are discussed, and a framework for reliability assessment of a new optical crack monitoring method is presented, emphasizing the influence of various uncertainty parameters, including long-term effects such as system ageing.
An assessment of the elastic-plastic buckling limit state for multi-strake wind turbine support towers poses a particular challenge for the modern finite element analyst, who must competently navigate numerous modelling choices related to the tug-of-war between meshing and computational cost, the use of solvers that are robust to highly nonlinear behaviour, the potential for multiple near-simultaneously critical failure locations, the complex issue of imperfection sensitivity and finally the interpretation of the data into a safe and economic design.
This paper reports on an international ‘round-robin’ exercise conducted in 2022 aiming to take stock of the computational shell buckling expertise around the world which attracted 29 submissions. Participants were asked to perform analyses of increasing complexity on a standardised benchmark of an 8-MW multi-strake steel wind turbine support tower segment, from a linear elastic stress analysis to a linear bifurcation analysis to a geometrically and materially nonlinear buckling analysis with imperfections. The results are a showcase of the significant shell buckling expertise now available in both industry and academia.
This paper is the first of a pair. The second paper presents a detailed reference solution to the benchmark, including an illustration of the Eurocode-compliant calibration of two important imperfection forms.
Meta-analysis of heat release and smoke gas emission during thermal runaway of lithium-ion batteries
(2023)
Herein a meta-analysis of 76 experimental research papers from 2000 to 2021 is given about possible effects on the thermal runaway of lithium-ion battery cells. Data on the hazards of gas emissions and released heat are related to each other and differentiated by cell properties such as, cell geometry, cathode type or state of charge. Quantitative information on the total heat release in the range of 2.0–112.0 kJ Wh−1, the peak heat release rate in the range of 0.006–2.8 kW Wh−1and the smoke gas emission were extracted, normalized in terms of cell energy (Wh), combined in a data library and compared graphically. The total amount of gas emitted (3–48 mmol Wh−1) as well as the released amount of carbon monoxide (1–161 mg Wh−1) and hydrogen fluoride (2–197 mg Wh−1) were investigated as a function of the state of charge and cell geometry. The analysis reveals that the measured values are significantly influenced by the types of calorimeters and smoke gas analyzers used as well as by the type of thermal runaway trigger. This meta-analysis can serve as an important basis for any risk assessment of lithium-ion batteries.
Polymers of intrinsic microporosity (PIMs) are promising candidates for the active layer in gas separation membranes due to their high permeability and reasonable permselectivity. These appealing properties originate from a microporous structure as a result of inefficient segment packing in the condensed state due to a combination of a ladder-like rigid backbone and sites of contortion. However, this class of polymers suffers from a significant decrease in the permeability with time due to physical aging, whereby typically, the permselectivity increases. The initial microporous structures approach a denser state via local rearrangements, leading to the reduction of the permeability. Hence, a detailed characterization of the molecular mobility in such materials can provide valuable information on physical aging. In this work, the dielectric behavior of PIM-1 films and their behavior upon heating (aging) were revisited by isothermal frequency scans during different heating/cooling cycles over a broad temperature range between 133 and 523 K (−140 to 250 °C). In addition, the obtained results were compared with data of samples that were annealed at ambient temperatures over different time scales. Multiple dielectric processes were observed: several relaxation processes due to local fluctuations and a Maxwell−Wagner−Sillars polarization effect related to the microporosity. The temperature dependence of the rates of all processes follows the Arrhenius law where the estimated activation energy depends on the nature of the process. The influence of the thermal history (aging) on the processes is discussed in detail.